ArticleBMC bioinformatics2023
Reconstructing B cell lineage trees with minimum spanning tree and genotype abundances.
Article in BMC bioinformatics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- deepNGS navigator: exploring antibody NGS datasets using deep contrastive learning.Bioinformatics (Oxford, England) · 2025Article
- AffMB: affinity maturation analysis with SHM-guided B-cell lineage trees.Bioinformatics (Oxford, England) · 2025Article
- New generalized metric based on branch length distance to compare B cell lineage trees.Algorithms for molecular biology : AMB · 2024Article
- Isotype-aware inference of B cell clonal lineage trees from single-cell sequencing data.Cell genomics · 2024Article
- B cell tolerance and autoimmunity: Lessons from repertoires.The Journal of experimental medicine · 2024Review
- Protocol for fast clonal family inference and analysis from large-scale B cell receptor repertoire sequencing data.STAR protocols · 2024Article
- B cell phylogenetics in the single cell era.Trends in immunology · 2024Review
- TRIBAL: Tree Inference of B cell Clonal Lineages.bioRxiv : the preprint server for biology · 2023Article
- ViCloD, an interactive web tool for visualizing B cell repertoires and analyzing intraclonal diversities: application to human B-cell tumors.NAR genomics and bioinformatics · 2023Article
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Authors and funding
5 authors.
Funding
Abstract
B cell receptor (BCR) genes exposed to an antigen undergo somatic hypermutations and Darwinian antigen selection, generating a large BCR-antibody diversity. This process, known as B cell affinity maturation, increases antibody affinity, forming a specific B cell lineage that includes the unmutated ancestor and mutated variants. In a B cell lineage, cells with a higher antigen affinity will undergo clonal expansion, while those with a lower affinity will not proliferate and probably be eliminated. Therefore, cellular (genotype) abundance provides a valuable perspective on the ongoing evolutionary process. Phylogenetic tree inference is often used to reconstruct B cell lineage trees and represents the evolutionary dynamic of BCR affinity maturation. However, such methods should process B-cell population data derived from experimental sampling that might contain different cellular abundances. There are a few phylogenetic methods for tracing the evolutionary events occurring in B cell lineages; best-performing solutions are time-demanding and restricted to analysing a reduced number of sequences, while time-efficient methods do not consider cellular abundances. We propose ClonalTree, a low-complexity and accurate approach to construct B-cell lineage trees that incorporates genotype abundances into minimum spanning tree (MST) algorithms. Using both simulated and experimental data, we demonstrate that ClonalTree outperforms MST-based algorithms and achieves a comparable performance to a method that explores tree-generating space exhaustively. Furthermore, ClonalTree has a lower running time, being more convenient for building B-cell lineage trees from high-throughput BCR sequencing data, mainly in biomedical applications, where a lower computational time is appreciable. It is hundreds to thousands of times faster than exhaustive approaches, enabling the analysis of a large set of sequences within minutes or seconds and without loss of accuracy. The source code is freely available at github.com/julibinho/ClonalTree.
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